Fixing and Cleaning Up Address Misspellings En Masse - Typical when Users Enter a City or State with Slightly Different Spellings

This article provides a quick walk-through on ‘normalizing’ addresses in your database so that slight misspellings are cleaned up en masse. Databases can get messy from time-to-time especially if there is a lot of activity taking place – instead of going one-by-one to clean up your address records, this article shows how to fix it with a mass update.

Scenario:as users enter data into the system or people come into your database through anonline donationorevent sign-upit’s possible that one of the address fields was entered slightly wrong e.g. city. This will cause the drop-downs in the database to contain inconsistent data. The example below shows the city Minneapolis spelt three different ways when only one of the ways is correct:

Run asearch queryby the misspelled address field i.e. City, State, Country, Street, Zipcode, etc. In my example I searched for the city “Minneapol” which should be Minneapolis which produced 10 results.

Tip:if you put quotes “” around the word it will only return exact matches which in this example was important.

Click the Edit drop-down at the top of the screen and select Set Fields….

Scroll down to the field in the list that is misspelled. Enter the correct spelling and click [OK]. In my example it was the City field.

Double-check that everything is correct and click [OK].

You’ll get a prompt when the process is finished. Click [OK] to proceed.

Run another search in the Address list by the same misspelled field (using quotes around it) and the results should equal zero. My example is below.

If you have a large database and/or you haven’t done this in a while it may take 15+ minutes for the process to complete.

Click [OK] once the process is finished.

Navigate back to the Contacts (Voters/Donors) list and verify that your drop-downs are cleaned up (if it’s not a field that’s a drop-down you can verify byformattingthe column into the grid). In my example the 2 misspelled cities for ‘Minneapolis’ have been cleaned and now the correctly spelled one is all that remains.

The related resources below link to a wide variety of other useful articles and videos related to cleaning up your database.